Addressing Technical Debt: A Growing Necessity for Federal Agencies

Image

The U.S. government’s Department of Government Efficiency (DOGE) was created to cut waste from government spending and improve efficiency by July 2026. Agencies have been asked to prove productivity and justify their budgets. For federal information technology (IT) departments, this means that it might be time to prioritize one of their biggest pain points: technical debt. The problem is that many organizations don’t have a common definition for technical debt, or they lack the resources to address its root causes. 

A costly and pervasive problem

An April 2025 Subcommittee on Cybersecurity, Information Technology, and Government Innovation hearing on Unlocking Government Efficiency Through IT Modernization found that approximately 80% of the federal government’s $100 billion IT and cybersecurity budget goes toward “operating and maintaining systems that include outdated, obsolete legacy systems.” A 2024 Wall Street Journal article noted that technical debt costs the United States $2.41 trillion a year, and a survey of technology leaders in the same year found that roughly 70% believe technical debt is their biggest hurdle to innovation. While it’s hard to fact-check all these numbers, most experts agree that this is an extremely costly problem that is very difficult to mitigate. 

The easiest way to explain technical debt is that it’s all the hardware and software within an organization that is currently at end-of-life or end-of-support. It’s also about the processes you put in place to manage them. And since products and software are being taken out of commission almost every day, technical debt accumulates continuously. The solution seems easy. Just update, right? However, the root cause of technical debt is not a person in a room deciding to waste government money. Because missions take priority, IT teams need to get things done quickly to ensure connectivity for missions, and there are competing projects and budgets within agencies. Managing technical debt falls into the compliance or hardening space, meaning “we’ll fix it when someone tells us we have to.” As a result, IT teams are unable to configure systems optimally, enable systems to scale or regularly review emerging technologies, standards and best practices. They lack the time and efficient processes to do this. 

The Risks Associated With Accumulating Technical Debt
Because technical debt grows exponentially over time, that “fix it later” mindset can translate into 10% to 20% annual increases in IT maintenance costs, not something you want when you have to justify your budget. As with many issues that build over time, seemingly benign issues snowball into significant waste when measured as a whole. 

Technical debt goes beyond just being a nuisance. Government networks also connect to other corporate and financial networks, meaning those unpatched issues can lead to huge breaches of personal and other sensitive data. According to the Qualys Threat Research Unit, 20% of federal agency assets contain high-risk end-of-support software. While that figure alone is concerning, the risk becomes more urgent considering that 48% of vulnerabilities on the Cybersecurity and Infrastructure Security Agency’s (CISA’s) Known Exploited Vulnerabilities list are found in end-of-support software. These legacy systems are not only unsupported—they are also four times more likely to be weaponized by attackers.

For federal agencies, this isn’t just a technical issue—it’s a national security risk. Outdated infrastructure creates ideal conditions for threat actors, including nation-states, to exploit known weaknesses in critical systems.

A Practical Plan To Manage Technical Debt in Federal Agencies
Federal agency networks are inherently complex and constantly evolving. Completely eliminating technical debt isn’t realistic—but managing it strategically is. The goal should be to minimize risk, prioritize upgrades that reduce operational burden and pursue wins that demonstrate the value of modernization without disrupting critical missions.

The bipartisan Modernizing Government Technology Reform Act (H.R. 2985) is a good start. It requires the Office of the Federal Chief Information Officer to report on legacy systems that pose the highest risk, and it shows that the federal government understands the scope of the issue. Agencies can get ahead of their technical debt by considering the following steps:

Step 1: Establish Baseline Inventory
Begin with a full audit of your agency’s IT environment, including hardware, software, configurations, dependencies and usage.

→ Why it matters: Many federal agencies still rely on outdated methods—like Excel spreadsheets, static Visio diagrams or manually updated documents—to track network assets. These tools quickly become obsolete in dynamic environments and often miss critical systems or connections. In fact, industry assessments suggest that up to 30% of enterprise network assets are unknown or undocumented at any given time, creating significant security blind spots.

Without a real-time, accurate inventory of your network, you can’t effectively secure, maintain or modernize it. You can’t plot a journey if you don’t know where you’re starting. Missing or incorrect data leads to unpatched systems, overlooked vulnerabilities and costly missteps. A current and comprehensive network inventory is the foundation for every step that follows—especially when aligning modernization efforts to mission-critical functions and reducing technical debt.

Step 2: Prioritize Based on Mission Risk
Use your baseline data to identify which assets are most critical to your agency’s mission and which pose the greatest risk due to age, configuration or exposure.

→ Why it matters: To truly prioritize risk, you need more than a list of outdated assets—you need to understand how data flows across the network. Every possible path a packet can take represents a potential exposure point. Without a detailed view of these paths, it’s impossible to accurately assess which vulnerabilities—especially known common vulnerabilities and exposures—pose a real threat to your environment.

Agencies often focus on whether a system is technically vulnerable but overlook whether that vulnerability is reachable from a threat actor’s perspective. An accurate network model allows you to distinguish between theoretical risk and exploitable risk, helping you align remediation efforts with mission-critical systems and real-world exposure. It’s not just about knowing what’s outdated—it’s about knowing what’s exposed.

Step 3: Target Quick Wins
Identify systems that are easiest to modernize without disrupting core services. Start with low-friction upgrades that deliver visible improvements in performance or security.

→ Why it matters: Quick wins depend on knowing what can be swapped or upgraded safely. Network data helps pinpoint standalone systems or low-dependency assets that are ideal for fast action.

Step 4: Replace With Intent and Validation
When planning replacements, model how changes will affect the broader environment. Should upgrades happen per site, per system or per data center? Simulate and validate intent before implementation.

→ Why it matters: In complex federal networks, even a small hardware or software replacement can trigger unintended changes in connectivity—introducing new security gaps or breaking mission-critical communications. That’s why accurate, detailed network data is essential not just before a change, but after it as well.

By running pre- and post-change verification checks, engineering teams can ensure that connectivity and performance remain as intended across the entire network following equipment modernization efforts.

Step 5: Validate What’s Working—and What’s Not
Continuously assess system health and performance using real-time monitoring and diagnostics. Automate the validation of configurations and service uptime.

→ Why it matters: Real-time network telemetry allows you to detect degraded performance or misconfigurations early. Data enables validation loops that ensure systems function as intended after upgrades.

Step 6: Institutionalize Software Upgrade Procedures
Create repeatable, data-informed processes for software patching and upgrades. Include checks for redundancies, compatibility and pre-deployment validation.

→ Why it matters: Consistent software life-cycle management relies on knowing exactly what’s installed, where and how it’s configured. Detailed inventory and performance data reduce upgrade risk and enable scale.

Step 7: Shift to Proactive Configuration Management
Move from periodic audits to continuous configuration monitoring, alerting IT teams of drift from known-good states.

→ Why it matters: In dynamic network environments, configuration drift is one of the most common—and most dangerous—sources of risk. Even small, unauthorized changes can create vulnerabilities, disrupt connectivity or break critical security controls. Periodic audits often miss these changes, leaving agencies exposed for weeks or months.

By shifting to continuous, proactive verification, IT teams can detect misconfigurations and deviations from baseline in real time—before they escalate into outages or security incidents.

Step 8: Speak the Same Language
Most IT teams in the government have their own processes and tools. While technical debt remediation efforts are designed to help identify duplicates and waste, that documentation won’t help much if future teams can’t understand it.

→ Why it matters: Effective technical debt remediation—and any large-scale IT initiative—requires alignment across teams. But that’s nearly impossible when each team operates from its own disconnected tools, diagrams or data sets. Having one standardized approach to presenting network data means that every IT team member—from entry level to leadership—can quickly understand the state of the network.

Unchecked technical debt undermines agency resilience and security. A data-driven, phased approach to modernization—anchored in precise, real-time network intelligence—enables federal agencies to reduce risk, optimize performance and build lasting operational confidence.

Scot Wilson is a manager of federal technical solutions architects at Forward Networks, where he specializes in pre-sales engineering for the federal market. He has also held leadership positions at Riverbed Technology, Cisco, the U.S. Air Force and General Dynamics Information Technology. He holds an MBA from Penn State University and a B.S. in computer science from Georgia Institute of Technology.